The present invention relates generally to the ability to determine the physical location of device within a network, and more particularly to a creation of fingerprint localization map for a WiFi-network to allow for localization of user receiving a signal from the WiFi network.
A number of fingerprint-based localization techniques have been developed for indoor localization. For example, some of these techniques utilize the existing infrastructures such as WiFi, WiMAX, FM, RFID, and Cellular to build the fingerprints. Some others take advantage of the naturally existing ambient signals such as acoustic spectrum, ambient light, and magnetic field.
WiFi-fingerprint-based localization has attracted attention because of the ubiquitous deployment of WiFi access points. However, heavy initial training, handling of temporal fluctuation of received signal strength (RSS), and device heterogeneity still hinder its wide acceptance as a practical solution to the indoor localization. The heavy initial training is a significant bottleneck of fingerprint localization. It is basically the high labor cost of the fingerprint map establishing process.
Another technical challenge is the temporal fluctuation of RSS. This is mostly due to channel noise, change of environment, and dynamic power controlling of WLANs. A large number of RSS scans from a plurality of reference points may be needed to alleviate this issue.